Bariatric Surgeon Ergonomics: A Comparison of Laparoscopy and Robotics.

INTRODUCTION: Bariatric surgery is routinely performed using laparoscopic and robotic approaches. Musculoskeletal injuries are prevalent among both robotic and laparoscopic bariatric surgeons. Studies evaluating ergonomic differences between laparoscopic and robotic bariatric surgery are limited. This study aims to analyze the ergonomic, physical, and mental workload differences among surgeons performing robotic and laparoscopic bariatric surgery. MATERIALS AND METHODS: All primary laparoscopic and robotic bariatric surgeries, Roux-en-Y gastric bypass, and sleeve gastrectomy between May and August 2022 were included in this study. Objective ergonomic analysis was performed by an observer evaluating each surgeon intraoperatively according to the validated Rapid Entire Body Assessment tool, with a higher score indicating more ergonomic strain. After each operation, surgeons subjectively evaluated their physical workload using the body part discomfort scale, and their mental workload using the surgery task load index. RESULTS: Five bariatric surgeons participated in this study. In total, 50 operative cases were observed, 37 laparoscopic and 13 robotic. The median total Rapid Entire Body Assessmentscore as a primary surgeon was significantly higher in laparoscopic (6.0) compared to robotic (3.0) cases (P < 0.01). The laparoscopic and robotic approaches had no significant differences in the surgeons' physical (body part discomfort scale) or mental workload (surgery task load index). CONCLUSIONS: This study identified low-risk ergonomic stress in surgeons performing bariatric surgery robotically compared to medium-risk stress laparoscopically. Since ergonomic stress can exist even without the perception of physical or mental stress, this highlights the importance of external observations to optimize ergonomics for surgeons in the operating room.

Context Matters: A Theory of Semantic Discriminability for Perceptual Encoding Systems.

People's associations between colors and concepts influence their ability to interpret the meanings of colors in information visualizations. Previous work has suggested such effects are limited to concepts that have strong, specific associations with colors. However, although a concept may not be strongly associated with any colors, its mapping can be disambiguated in the context of other concepts in an encoding system. We articulate this view in semantic discriminability theory, a general framework for understanding conditions determining when people can infer meaning from perceptual features. Semantic discriminability is the degree to which observers can infer a unique mapping between visual features and concepts. Semantic discriminability theory posits that the capacity for semantic discriminability for a set of concepts is constrained by the difference between the feature-concept association distributions across the concepts in the set. We define formal properties of this theory and test its implications in two experiments. The results show that the capacity to produce semantically discriminable colors for sets of concepts was indeed constrained by the statistical distance between color-concept association distributions (Experiment 1). Moreover, people could interpret meanings of colors in bar graphs insofar as the colors were semantically discriminable, even for concepts previously considered "non-colorable" (Experiment 2). The results suggest that colors are more robust for visual communication than previously thought.